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Questions tagged [arima]

ARIMA (AutoRegressive Integrated Moving Average) model is a statistical model for finding patterns in time series in order to predict future points in the series.

In time series analysis, ARIMA (AutoRegressive Integrated Moving Average) model is a statistical model for finding patterns in time series in order to predict future points in the series (forecasting).

If your question concerns theoretical topics on ARIMA or practical topics which are not about implementation you might want to ask the question on cross validated.

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Errors in ARIMA models

I want to fetch MAPE error of arima model after fitting model. below is the summary of arima model Series: train ARIMA(1,1,1) Coefficients: ar1 ma1 0.4472 -0.925 s.e. 0.0310 0.014 sigma^2 estimated as 211188552: log…
learner
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Determining ARIMA frequency of non-stationary time series

I am trying to use ARIMA to forecast chemical concentrations in water tanks. I have a large dataset of around a million intervals, two minutes apart. When i use the autoarima in R i get a forecast looking like this: Forecast As you can see, it evens…
Søren Andersen
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How to forecast revenue when there is little data available?

I have quarterly revenues of an organisation from 2014 third quarter till 2017 second quarter, how to forecast revenue for 2018 quarters having this much data?
Naresh Verma
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reference of ARIMA in python

I used statsmodels.tsa.arima_model import ARIMA in Python to develop an ARIMA model. Recently I am writing the methodology of ARIMA, but I can not find any reference on the page. So here my question is where could I find the reference (or formula)…
Queena
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Forecast package in R ARIMA, what went wrong in this script?

I ran a set of R-commands with the given data (basically extracted from airpassenger data of box jenkins) and I ran into an error which I cannot apprehend. library(forecast) listr <- c(278.0, 284.0, 277.0, 317.0, 313.0, 318.0, 374.0, 413.0, 405.0,…
Biswajit Jana
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Null class to Date-time Class for qplot in R

I have a csv file with 2 coloumns-price and date.I am trying to do time series forecasting and for that I need to convert the date coloumn to date-time class. Presently the class of Date coloumn is NULL.I tried to convert it to character format,but…
Bunty
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Forecasting Time series data using ARIMA model when data contains only HH:MM:SS in python

I have a Dataframe that contains Time as index in the format of HH:MM:SS. The dataframe has only one column say Y which contains a float value. My Data set is : 09:37:57 121 09:39:05 73 09:40:40 91 09:40:45 …
M. Paul
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How to combine an output from a forecast thats in a loop

Im trying to build a rolling multistep ARIMA forecast. But I cant combine the outputs from the forecast with newer ones. from pandas import read_csv from statsmodels.tsa.arima_model import ARIMA data = read_csv('data_woc.csv', header=0,…
usama_khurshid
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How to find the p,d,q values selected in auto_arima() Python?

I would like to run auto_arima() on a training set and then use the same selected p,d,q values to evaluate arima() on a test set.
peebs96
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Why P,D,Q terms are taken into account into a SARIMAX model with 0 periodicity?

I am curious if someone noted this aspect of SARIMAX class of statsmodels library and can share an opinion about the fact that it is not ignoring the seasonal parameters when periodicity is…
crbl
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NameError: name 'timseseries' is not defined

from statsmodels.tsa.stattools import adfuller def test_stationarity(timeseries): #Determining rolling statistics rolmean = timseseries.rolling(window=9).mean() rolstd = timeseries.rolling(window=9).std() #Plotting rolling statistics orig =…
Prriyankaa A Singh
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how to perform data exploration on 1000 unique timeseries data?

This is the first time i am working on time series, hence kindly pardon me. My dataset consists of following, product id column with 1000 different products, date column, sales column. Since the first step will be to perform data exploration(time…
AVR
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which algorithm is suited for my time series data?

I am working in monitoring team, we do monitor of our client load on our tools. We recorded latency with respective to timeseries. Initially, I kept a static threshold to raise the anomaly detection. However, it doesn't work if seasonality occurs.…
sai sasank
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Predit price for put and call options?

I have to predict to purchase or not of the sp500 put and call options, however I do not understand some parts of the code that was provided to me. In addition can you explain to me what every option of the data does, for…
bibio95100
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